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Loss Functions

122 directly classified papers

Papers per year

Papers

Learning Augmentation Network via Influence Functions CVPR 2020
Learning From Noisy Anchors for One-Stage Object Detection CVPR 2020
Severity-Aware Semantic Segmentation With Reinforced Wasserstein Training CVPR 2020
Dice Loss for Data-imbalanced NLP Tasks ACL 2020
On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks AAAI 2020
Using Context in Neural Machine Translation Training Objectives ACL 2020
Token-level Adaptive Training for Neural Machine Translation EMNLP 2020
Addressing Exposure Bias With Document Minimum Risk Training: Cambridge at the WMT20 Biomedical Translation Task EMNLP 2020
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression AAAI 2020
Region Normalization for Image Inpainting AAAI 2020
Mis-Classified Vector Guided Softmax Loss for Face Recognition AAAI 2020
Hierarchical Modes Exploring in Generative Adversarial Networks AAAI 2020
Softmax Dissection: Towards Understanding Intra- and Inter-Class Objective for Embedding Learning AAAI 2020
Stochastic Loss Function AAAI 2020
Distribution-Aware Coordinate Representation for Human Pose Estimation CVPR 2020
Channel Attention Based Iterative Residual Learning for Depth Map Super-Resolution CVPR 2020
Circle Loss: A Unified Perspective of Pair Similarity Optimization CVPR 2020
Rotation Consistent Margin Loss for Efficient Low-Bit Face Recognition CVPR 2020
An Investigation Into the Stochasticity of Batch Whitening CVPR 2020
A Context-Aware Loss Function for Action Spotting in Soccer Videos CVPR 2020
Multi-Similarity Loss With General Pair Weighting for Deep Metric Learning CVPR 2019
Inter-Class Angular Loss for Convolutional Neural Networks AAAI 2019
Class-Balanced Loss Based on Effective Number of Samples CVPR 2019
P2SGrad: Refined Gradients for Optimizing Deep Face Models CVPR 2019
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack CVPR 2019